IT Infrastructure Library Training Classes in Lexington, Kentucky
Learn IT Infrastructure Library in Lexington, Kentucky and surrounding areas via our hands-on, expert led courses. All of our classes either are offered on an onsite, online or public instructor led basis. Here is a list of our current IT Infrastructure Library related training offerings in Lexington, Kentucky: IT Infrastructure Library Training
IT Infrastructure Library Training Catalog
Course Directory [training on all levels]
- .NET Classes
- Agile/Scrum Classes
- AI Classes
- Ajax Classes
- Android and iPhone Programming Classes
- Blaze Advisor Classes
- C Programming Classes
- C# Programming Classes
- C++ Programming Classes
- Cisco Classes
- Cloud Classes
- CompTIA Classes
- Crystal Reports Classes
- Design Patterns Classes
- DevOps Classes
- Foundations of Web Design & Web Authoring Classes
- Git, Jira, Wicket, Gradle, Tableau Classes
- IBM Classes
- Java Programming Classes
- JBoss Administration Classes
- JUnit, TDD, CPTC, Web Penetration Classes
- Linux Unix Classes
- Machine Learning Classes
- Microsoft Classes
- Microsoft Development Classes
- Microsoft SQL Server Classes
- Microsoft Team Foundation Server Classes
- Microsoft Windows Server Classes
- Oracle, MySQL, Cassandra, Hadoop Database Classes
- Perl Programming Classes
- Python Programming Classes
- Ruby Programming Classes
- Security Classes
- SharePoint Classes
- SOA Classes
- Tcl, Awk, Bash, Shell Classes
- UML Classes
- VMWare Classes
- Web Development Classes
- Web Services Classes
- Weblogic Administration Classes
- XML Classes
- RED HAT ENTERPRISE LINUX AUTOMATION WITH ANSIBLE
18 February, 2025 - 21 February, 2025 - Docker
3 February, 2025 - 5 February, 2025 - DOCKER WITH KUBERNETES ADMINISTRATION
17 March, 2025 - 21 March, 2025 - Object Oriented Analysis and Design Using UML
9 June, 2025 - 13 June, 2025 - RHCSA EXAM PREP
16 June, 2025 - 20 June, 2025 - See our complete public course listing
Blog Entries publications that: entertain, make you think, offer insight
Since its foundation, HSG has been a leader in Business Rule Management Systems Training and Consulting services by way of the Blaze Advisor Rule Engine. Over the years we have provided such services to many of the worlds largest corporations and government institutions whose respective backgrounds include credit card processing, banking, insurance, health and medicine and more, much more. Such training and consulting services have included:
Create a wrapper object model in either Java, .NET or XML
Identify and catalog business rules
Develop a rule architecture within Blaze Advisor that isolates rule repositories as they relate to functionality and corporate policies
Configure, develop and implement a variety of interfaces to the rule engine from disparate systems ranging from mainframe applications written in Cobol to UNIX/Windows applications using Enterprise Java Beans, Windows Services, Web Services, Fat Clients, Java Messaging Services and Web Applications.
Review and update code to boost efficiency either by way of
Removing functions calls within conditional statements
Ensuring that database calls are essential or can be rearchitected in some other manner
Employing the rete algorithm where necessary
Paring down extensively large class models
Deploying such appliations in multi-threaded systems
· ...
Call us if you:
are in need of Blaze Advisor Expertise
are developing SMEs in Blaze
want to speak directly with an expert (no placement agencies)
want an affordable alternative to FICO
want to work with an industry leader
C TRAINING – THE THREE MAIN STAGES OF PROGRAMMING DEVELOPMENT
If you are an aspiring programmer, learning about programming in C is one of the most integral steps of your development. It is essential that you get the highest quality C training, so that you are well-grounded in the language, and are going to be able to fulfill most of your programming and developmental tasks. Learning about all aspects of the programming language, including how to fully utilize its portability and design will help you to secure your future in computer programming. These are some of the concepts you should familiarize yourself with:
· Major elements of the programming language – This includes things like libraries of functions, using data flow control, and a thourough examination of the basic data types the language is able to address. As you learn about these fundamental elements, make sure to get practical experience during the course of your C training also, by actually writing programs that follow whatever curriculum you have chosen.
· Different techniques and other programming elements – Different series of coursework choose to emphasize different things, but try to learn as much as you can about different techniques that are actually employed. Manipulating both characters and strings, allocating dynamic memory in the proper manner, defining macros, and utilizing the runtime library are all examples of these elements.
Machine learning systems are equipped with artificial intelligence engines that provide these systems with the capability of learning by themselves without having to write programs to do so. They adjust and change programs as a result of being exposed to big data sets. The process of doing so is similar to the data mining concept where the data set is searched for patterns. The difference is in how those patterns are used. Data mining's purpose is to enhance human comprehension and understanding. Machine learning's algorithms purpose is to adjust some program's action without human supervision, learning from past searches and also continuously forward as it's exposed to new data.
The News Feed service in Facebook is an example, automatically personalizing a user's feed from his interaction with his or her friend's posts. The "machine" uses statistical and predictive analysis that identify interaction patterns (skipped, like, read, comment) and uses the results to adjust the News Feed output continuously without human intervention.
Impact on Existing and Emerging Markets
The NBA is using machine analytics created by a California-based startup to create predictive models that allow coaches to better discern a player's ability. Fed with many seasons of data, the machine can make predictions of a player's abilities. Players can have good days and bad days, get sick or lose motivation, but over time a good player will be good and a bad player can be spotted. By examining big data sets of individual performance over many seasons, the machine develops predictive models that feed into the coach’s decision-making process when faced with certain teams or particular situations.
General Electric, who has been around for 119 years is spending millions of dollars in artificial intelligence learning systems. Its many years of data from oil exploration and jet engine research is being fed to an IBM-developed system to reduce maintenance costs, optimize performance and anticipate breakdowns.
Over a dozen banks in Europe replaced their human-based statistical modeling processes with machines. The new engines create recommendations for low-profit customers such as retail clients, small and medium-sized companies. The lower-cost, faster results approach allows the bank to create micro-target models for forecasting service cancellations and loan defaults and then how to act under those potential situations. As a result of these new models and inputs into decision making some banks have experienced new product sales increases of 10 percent, lower capital expenses and increased collections by 20 percent.
Emerging markets and industries
By now we have seen how cell phones and emerging and developing economies go together. This relationship has generated big data sets that hold information about behaviors and mobility patterns. Machine learning examines and analyzes the data to extract information in usage patterns for these new and little understood emergent economies. Both private and public policymakers can use this information to assess technology-based programs proposed by public officials and technology companies can use it to focus on developing personalized services and investment decisions.
Machine learning service providers targeting emerging economies in this example focus on evaluating demographic and socio-economic indicators and its impact on the way people use mobile technologies. The socioeconomic status of an individual or a population can be used to understand its access and expectations on education, housing, health and vital utilities such as water and electricity. Predictive models can then be created around customer's purchasing power and marketing campaigns created to offer new products. Instead of relying exclusively on phone interviews, focus groups or other kinds of person-to-person interactions, auto-learning algorithms can also be applied to the huge amounts of data collected by other entities such as Google and Facebook.
A warning
Traditional industries trying to profit from emerging markets will see a slowdown unless they adapt to new competitive forces unleashed in part by new technologies such as artificial intelligence that offer unprecedented capabilities at a lower entry and support cost than before. But small high-tech based companies are introducing new flexible, adaptable business models more suitable to new high-risk markets. Digital platforms rely on algorithms to host at a low cost and with quality services thousands of small and mid-size enterprises in countries such as China, India, Central America and Asia. These collaborations based on new technologies and tools gives the emerging market enterprises the reach and resources needed to challenge traditional business model companies.
Let’s face it, fad or not, companies are starting to ask themselves how they could possibly use machine learning and AI technologies in their organization. Many are being lured by the promise of profits by discovering winning patterns with algorithms that will enable solid predictions… The reality is that most technology and business professionals do not have sufficient understanding of how machine learning works and where it can be applied. For a lot of firms, the focus still tends to be on small-scale changes instead of focusing on what really matters…tackling their approach to machine learning.
In the recent Wall Street Journal article, Machine Learning at Scale Remains Elusive for Many Firms, Steven Norton captures interesting comments from the industry’s data science experts. In the article, he quotes panelists from the MIT Digital Economy Conference in NYC, on businesses current practices with AI and machine learning. All agree on the fact that, for all the talk of Machine Learning and AI’s potential in the enterprise, many firms aren’t yet equipped to take advantage of it fully.
Panelist, Michael Chui, partner at McKinsey Global Institute states that “If a company just mechanically says OK, I’ll automate this little activity here and this little activity there, rather than re-thinking the entire process and how it can be enabled by technology, they usually get very little value out of it. “Few companies have deployed these technologies in a core business process or at scale.”
Panelist, Hilary Mason, general manager at Cloudera Inc., had this to say, “With very few exceptions, every company we work with wants to start with a cost-savings application of automation.” “Most organizations are not set up to do this well.”
Tech Life in Kentucky
Company Name | City | Industry | Secondary Industry |
---|---|---|---|
Brown-Forman Beverages Worldwide | Louisville | Manufacturing | Alcoholic Beverages |
General Cable Corporation | Newport | Computers and Electronics | Semiconductor and Microchip Manufacturing |
PharMerica Corporation | Louisville | Software and Internet | Data Analytics, Management and Storage |
Humana Inc. | Louisville | Financial Services | Insurance and Risk Management |
Lexmark International, Inc. | Lexington | Computers and Electronics | Peripherals Manufacturing |
YUM! Brands, Inc. | Louisville | Retail | Restaurants and Bars |
ResCare, Inc. | Louisville | Healthcare, Pharmaceuticals and Biotech | Doctors and Health Care Practitioners |
Kindred Healthcare, Inc. | Louisville | Healthcare, Pharmaceuticals and Biotech | Residential and Long-Term Care Facilities |
Ashland Inc | Covington | Manufacturing | Chemicals and Petrochemicals |
training details locations, tags and why hsg
The Hartmann Software Group understands these issues and addresses them and others during any training engagement. Although no IT educational institution can guarantee career or application development success, HSG can get you closer to your goals at a far faster rate than self paced learning and, arguably, than the competition. Here are the reasons why we are so successful at teaching:
- Learn from the experts.
- We have provided software development and other IT related training to many major corporations in Kentucky since 2002.
- Our educators have years of consulting and training experience; moreover, we require each trainer to have cross-discipline expertise i.e. be Java and .NET experts so that you get a broad understanding of how industry wide experts work and think.
- Discover tips and tricks about IT Infrastructure Library programming
- Get your questions answered by easy to follow, organized IT Infrastructure Library experts
- Get up to speed with vital IT Infrastructure Library programming tools
- Save on travel expenses by learning right from your desk or home office. Enroll in an online instructor led class. Nearly all of our classes are offered in this way.
- Prepare to hit the ground running for a new job or a new position
- See the big picture and have the instructor fill in the gaps
- We teach with sophisticated learning tools and provide excellent supporting course material
- Books and course material are provided in advance
- Get a book of your choice from the HSG Store as a gift from us when you register for a class
- Gain a lot of practical skills in a short amount of time
- We teach what we know…software
- We care…